The subject matter disclosed herein relates to the use of energy-resolved photon-counting detectors.
Non-invasive imaging technologies allow images of the internal structures or features of a subject (patient, manufactured good, baggage, package, or passenger) to be obtained non-invasively. In particular, such non-invasive imaging technologies rely on various physical principles, such as the differential transmission of X-rays through the target volume or the reflection of acoustic waves, to acquire data and to construct images or otherwise represent the internal features of the subject.
For example, in X-ray-based imaging technologies, X-ray radiation spans a subject of interest, such as a human patient, and a portion of the radiation impacts a detector where the intensity data is collected. In X-ray systems, a photodetector produces signals representative of the amount or intensity of radiation impacting discrete pixel regions of a detector surface. The signals may then be processed to generate an image that may be displayed for review.
In one such X-ray-based technique, known as computed tomography (CT), a scanner may project fan-shaped or cone-shaped X-ray beams from one or more X-ray sources at numerous view angle positions about an object being imaged, such as a patient. The X-ray beams are attenuated as they traverse the object and are detected by a set of detector elements which produce signals representing the intensity of the incident X-ray beams on the detector. The signals are processed to produce data representing the line integrals of the linear attenuation coefficients of the object along the X-ray paths. These signals are typically called “projection data” or just “projections”. By using reconstruction techniques, such as filtered backprojection, images may be generated that represent a volume or a volumetric rendering of a region of interest of the patient or imaged object. In a medical context, pathologies or other structures of interest may then be located or identified from the reconstructed images or rendered volume.
Conventionally, radiation detectors used in these types of imaging techniques operate in an energy-integrating mode (i.e., readout of the total integrated energy deposited during an acquisition interval) or a photon-counting mode (each individual X-ray photon is detected). Energy integration is the conventional mode for reading out X-ray detectors in most clinical applications. However, energy-integrating readout approaches operate poorly in low-flux imaging applications, where electronic noise associated with the detector readout operation may overwhelm the available signal.
In some applications, individual X-ray photon counts are of more interest than the total integrated energy information associated with energy-integrating approaches. Conventional scintillator-based photon-counting modes utilize silicon photomultipliers (SiPMs) that are expensive and not practical for high count rate applications such as CT; such technology is used with positron emission tomographic systems. Further, such photon-counting approaches may be limited in the type of information they produce, such as yielding only the raw photon count number without associated energy information.
In contrast, certain techniques, such as dual-energy (e.g., high- and low-energy imaging) and/or material-decomposition imaging, benefit not only from photon counts in a generic sense, but from obtaining spectral information, i.e., energy information, for a given exposure event. That is, such techniques generate photon counts that are separated into respective energy bins, and thus discriminate between photon events at different energies, thereby characterizing or counting the number of photons observed at different photon energy ranges. To address this need, certain energy-discriminating, photon-counting X-ray detector technologies may be employed. In certain instances, such approaches employ a detection medium that directly converts incident X-rays to measurable signal (i.e., electron-hole pairs as with direct conversion materials), as opposed to techniques employing a scintillator-based intermediary conversion and subsequent detection of the generated optical photons.
However, the practical use of such photon-counting, energy-discriminating detectors still face certain technical challenges. One such challenge is the count-rate capability. When the photon flux is too high, the energy information associated with the detected signal gets distorted due to the pile-up effect (photons arrive too quickly for their energy to be properly characterized—the photons “pile up” in the detector). Existing approaches to address this issue, e.g. utilizing filters providing a short shaping time, can differentiate the incident events that occur within a short time interval, but can also lead to incomplete signal (charge) collection within the sensor and increased sensitivity to the cross-talk (i.e., transient) signal observed in adjacent detector channels.
A second challenge of photon-counting, energy-discriminating detectors is the charge-sharing effect. When an incident photon interaction occurs near the edge of a detector pixel, it creates a signal either by multiple X-ray interactions (i.e., K-escape, Compton scatter) or by charge sharing (i.e., electron cloud sharing) across the pixel boundary and is thus detected by multiple pixels, i.e., the respective signal in each of the effected pixels. This effect degrades the energy resolution by causing a low-energy tail in the spectral response function. To address this problem, it has been proposed to use coincidence logic to identify multiple-pixel events and digitally sum the signal of the neighboring pixels. To clarify, coincidence logic estimates the arrival time of a photon and determines if multiple detector pixels in a local neighborhood detect this event. If so, the energy from the neighboring pixels is summed, and the associated counter in the pixel containing the centroid of the detected energy is incremented.
However, the present approaches to address both of these challenges leads to a further issue. In particular, when a detection event occurs near the boundary between two pixels, resulting in uneven amounts of signal in the two pixels due to charge sharing, the coincidence logic can correctly identify and sum the two signals with a small quantity of signal loss. However, if the incident photon interaction occurs entirely within one of the pixels (with no charge-sharing occurring), the weighting potential crosstalk (i.e. transient signal) may be mistaken by the coincidence logic as charge sharing and may erroneously result in a summing operation being performed, potentially causing an overestimation of the detected signal.